What You'll Do:

Job summary

The AI Solutions Engineer will design, build, test, and deploy AI enabled tools that improve the efficiency, consistency, and execution of Eaton's engineering processes.

This role sits within Engineering Operational Excellence (EFE OPEX) and focuses on hands on development of AI solutions embedded directly into engineering workflows, such as engineering planning, NPI / Product Development tasks execution, DFMEA/PFMEA, engineering knowledge access, and reporting.

The role works closely with EFE Digital and IT to implement AI solutions using Eaton approved platforms and standards. The primary accountability is delivery and adoption of working AI tools that engineers use in their day to day work. This role does not own enterprise AI strategy or platform governance.

Job responsibilities

AI Solution Development (Primary Focus)

Design and hands on build AI solutions that support engineering operational processes, including:
Engineering planning and scheduling
NPI / PROLaunch execution support
DFMEA / PFMEA drafting and consistency checks
Engineering knowledge retrieval using RAG (with citations)
Design review action tracking and reporting
Implement AI workflows using Azure OpenAI, Azure AI Foundry, and Eaton approved AI frameworks.

Implementation & Integration

Develop end to end AI solutions, including:
prompt logic and AI agent workflows
data preparation and retrieval
basic orchestration and error handling
integration into Microsoft Teams, SharePoint, or existing engineering tools
Partner with IT to ensure solutions comply with:
security and identity requirements
logging and auditability standards
Eaton AI guardrails and deployment practices

Cross Functional Collaboration

Work closely with:
EFE Digital on AI capabilities embedded in engineering and PLM adjacent tools
IT on infrastructure, APIs, and deployment pipelines
Translate engineering process needs to clear technical requirements and user stories.

Adoption & Continuous Improvement

Pilot AI tools with engineering users and collect feedback
Iterate solutions to improve usability, reliability, and value
Support basic documentation, demos, and user enablement activities

Qualifications:

Bachelor's degree in computer science, engineering, or related field. A master's degree in AI, Machine Learning, or Data Science is preferred.
4-7 years of experience in software development, automation, or digital solution engineering

Skills:

Hands on experience with: Python, APIs and cloud based services, Azure environment (preferred)
Demonstrated ability to build and deploy working solutions, not just proofs of concept

Preferred Qualifications:

Experience working in an engineering, industrial, or manufacturing environment
Familiarity with:
Engineering workflows such as NPI, project management, quality, or documentation
AI assistants, RAG patterns, or workflow based AI solutions
Comfortable working directly with process owners and end users

Skills:

Strong analytical, problem solving, and data driven decision making skills.
Excellent communication ability to translate complexity into clear narratives.
Ability to collaborate in a global, cross functional engineering environment.

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